My name is Eileen Liang, and I'm a rising sophomore at Roy C. Ketcham High School in upstate NY. I'm looking forward to an extremely positive and educationally stimulating session at BLI! Not only am I excited for the content of the camp, but am also anticipating working alongside other such motivated and intelligent students. Quickly following my introduction the biology in my freshman year, I've become intrigued by biology. Not only has biology quickly become my favorite subject, but the fact that biology is very literally the science of all living things around us has only fueled my passion for the subject. Although I won't be taking AP bio until my junior year, I'm already looking forward to expanding my knowledge of bio and hope to become more involved with biology research. I feel that biology research is extremely relevant in order to continue to improve on modern societies, and the constant additions and revelations found as a result of research is truly motivating and impressive.
I pride myself in my participation in a number of school clubs and teams. For example, I have been on and played second singles on my school's varsity tennis team for 3 years and have made both regionals and sectionals for two of those years. Similarly, I participate in my school Interact team, Model UN and debate club, Science Olympiad, and am the treasurer of our school math team, which placed second at sectionals. Also, over the past year, I have collaborated with three other individuals in order to create a fencing club at our school. Through my participation in these activities, I have thoroughly enjoyed the company of unique and talented individuals as well as the knowledge and collaborative qualities that have come as a result of these activities. A random fact about me is that I work three jobs, and thoroughly enjoy each one of them, such as being a Kumon instructor, a traditional Chinese dance instructor at my local Chinese school and teaching novice tennis at Cross Court Tennis Club.
Biology has long since progressed since its rudimentary beginnings in archaic time periods, fueled by the interests of scientists and researchers to explicate the phenomenons presented by the natural world. However, even despite the numerous and groundbreaking results that have stemmed from researching biology, the potential that the field still holds is almost impossible to measure. One such example arises from the emergence of synthetic biology, a field that only recently has come to light, however the possibilities that stem from it have already begun to shape the future of many industries. One of the most revolutionary idea that was derived from the occurrence of such a field was the ability to utilize manipulation of bacteria in order to compute and solve complex math problems, which would later become known as bacterial computing. One of the first utilization of this technology was through solving the Hamiltonian Path Problem, which upon completion, demonstrated the possibility of using such bacteria to solve a number of issues. The future of bacterial computing is extremely promising, and the complex technology has already been employed by both biologists and engineers in order to diagnosis cancer in early stages.
Hamiltonian Path Problem
The inception of bacterial computing ultimately began when Adleman successfully manipulated the E. coli bacteria to solve a complex math problem known as the Hamiltonian Path Problem (HPP) using seven nodes. This contribution to biology became the essential first in consolidating the ideas of bacterial computing, demonstrating and analyzing the possible options that allowed for the beginnings of the new field. To explain, the Hamilton Path Problem (HPP) occurs as a problem within the mathematical field of graph theory and essentially concerns determining a path (if any) that would pass through all the vertices in an undirected or directed graph. Similarly, the HPP is classified as a NP-complete (nondeterministic polynomial) in which any solutions could easily be proven correct.
The relevance of bacterial computing is justified through its innumerable advantages. The autonomous nature of bacteria, for example, would not necessitate human intervention, and the exponential growth of bacteria would assure and even strengthen the number of processors available to solve a particular problem. Similarly, the ability for bacteria to evolve in changing conditions or in response to challenges demonstrate the versatility of bacterial computing. Not only are bacteria ideal organisms for computation, the process of cell division matches the abilities of a conventional silicon computer algorithm. Not only can the bacteria be programmed in such a way that mimics the parallel processing and increased number of processors that are utilized in current computer algorithms, the alternative choice offers many more options that easily demonstrate more potential than that of the conventional methods.
The usage of mathematical modeling was extremely relevant in conducting the research that allowed for the HPP to be solved using bacterial computing. One such example included questioning of whether the initial orientation and order of the DNA would affect the probability of uncovering a solution to the HPP. In the HPP experiment, many bacteria would be searching for a viable solution through flipping genes catalyzed by the Hin recombinase. Under the assumption that each reversal of adjacent DNA edges was equally likely, the team was able to determine that the probability that any starting configuration would be in the solution state after k flips using a transition matrix. By using this matrix, the scientists were able to find, for example, that a three node and three edge graph could converge to equilibrium quickly at 1/48 (.02 seconds) in approximately 20 flips. These computations demonstrated the feasibility of the experiment, as E. coli could divide every 20 - 30 minutes, and would exceed 20 flips in around 16 hours, even if the Hin recombinase were only to catalyze one reaction per cell cycle. Similarly, it was necessary for researchers to use mathematical modelling in order to determine how many bacteria would be required in order to assure at least one cell with a solution. The result to these questions determined that almost 1 billion plasmids would be required in order to guarantee a 99.9% confidence that one of them would contain a HPP solution.
With that said, in order to solve the HPP, E. coli bacteria were basically transformed into computers that could be programmed to execute algorithms through gene circuits. Furthermore, it was necessary for the bacteria to have the ability to be observed as well as sensitive to the environment. To start, three nodes containing edges on a directed graph were encoded into DNA and immediately shuffled inside a bacterium by a recombination system. Genes were also used as nodes that would fluoresce based on red or green proteins, and researchers then utilized the phenotypes that would express the random ordering of graph edges. If the clones showed success, they would fluoresce yellow, as a result of the combination of red and green fluorescence.
At this point, it became necessary for the team to implement certain abstractions in order to design the bacteria. For example, the DNA segments were used to depict nodes on the directed graph, and were bordered by hixC sites which could be rearranged by the Hin recombinase to generate a random orientation of the edges on the graph. In a second abstraction, each gene, besides the terminal one, was regarded as a split gene (in two). Based on this, a DNA edge terminating on the node would be the location of a five half of a gene, while the DNA edge originating on the node would house a three half of a gene. Similarly, a third abstraction presented a new phenotype by representing a solution to the Hamilton Path Problem with a particular arrangement of DNA.
To begin their first implementation after they were confident of positive results, the researchers began with a simple three node model. For observational purposes, they utilized the RFPs and GFPs as nodes and markers. Between them, hixC sites were placed in order for recombination to occur. The function of the GFP and RFP allowed for the scientists to insert these sites without forfeiting the fluorescence. By inserting these sites, the Hin recombinase would be able to bind to them and in turn, flip or invert the DNA.
From there, by employing the now genetically modified E. coli bacteria, the team began to conduct their proof-of-concept experiment. With a unique Hamiltonian pathway, beginning at the RFP node and travelling via pathway A to the GFP, followed by travel from the GFP to the double transcription terminator, which represented the ending of the pathway, along path B. C, on the other hand, acted as a detractor rather than a path, and diverted the pathway from the RFP to the double transcription terminator. After the successful results from this experiment, the three node three edge model would later be put to use as the control, utilizing the three edges to create DNA constructs.
Preceding the application of the Hin recombinase, expression cassettes were made from the previously existing DNA constructs. Each of these cassettes had the same makeup, consisting of a T7 bacteriophage RNA polymerase promoter, a ribosome binding site, and the 5 half of the RFP node before the first hixC site. After adding edges, the constructs that resulted from the arrangement were named ( ABC, ACB, and BAC), each of which corresponded to a certain phenotype that was expressed in that particular experiment.
Following the successful results from the first experiment, researchers later conducted a multitude of similar experiments involving finding the solutions to the Hamiltonian Path Problem. Not only were they able to demonstrate the modification of bacteria (E. coli) in order to solve complex math problems such as the Hamiltonian Path Problem, but also paved the way to the endless possibilities of bacterial computing.
Design
As demonstrated in the information above, bacterial computing is a highly complex and the future of the field is increasingly promising. Currently, researchers and engineers have worked to utilize the modern technology in order to put it to practical use. In terms of this design project, we will utilize some of the concepts used in bacterial computing such as the implementation of information into bacteria in order to diagnosis gastric cancer.
Gastric cancer, is the formation of malignant cells in the mucosal lining of the stomach, and is more commonly called adenocarcinoma. Similar to the other forms of cancer, the disease begins when a mutation arises in a cell’s DNA and begins to rapidly spread and proliferate. Unlike normal cells, however, these malignant cells do not participate in the normal cell cycle, and completely avoid apoptosis. As a result, these abnormal cells form tumors and after sufficient accumulation, will metastasize and spread to other tissues in the body. Early detection of gastric cancer is often difficult, as the symptoms arise only in the later stages of the disease. Thus, the early diagnosis of adenocarcinoma would be extremely relevant and would immensely increase treatment of the disease. Although it is not prevalent in the United States, gastric cancer is still immensely relevant on a worldwide scale, particularly in developing countries.
Our design project revolves around utilizing Bacteroides thetaiotaomicron bacteria in order to detect the presence of Helicobacter pylori, which also resides in the gut. The former is a kind of bacteria that thrives in the gut, and is actually the most abundant bacteria that resides there. Bacteroides thetaiotaomicron is capable of hydrolyzing indigestible polysaccharides, and also contains an environment sensing membrane that is made up primarily of membrane proteins. H. pylori however, is a bacteria that has coexisted with humans for large amounts of time, and the spiral shaped bacterium lives in the mucosal lining of the stomach. In order to survive in the harsh environment of the stomach, H. pylori secretes the enzyme urease, which converts urea to ammonia, and in turn neutralizes the acidity of the environment. Though the majority of people infected with the H. pylori bacteria will never experience illnesses directly caused by the bacterium, recent studies have labelled the bacteria as a major risk factor for both peptic ulcer disease as well as non-cardia gastric cancer. For example, recent research has determined that those who were infected by the bacteria were eightfold more likely to develop adenocarcinoma. This is most likely due to the release of the toxin CagA which alters the structure of stomach cells in order to host the H. pylori. Although a large majority of H. pylori do not have this ability, the bacteria that evade immune responses are able to inject the toxin using an almost needle like appendage. As the levels of CagA increase, the chronic inflammation that eventually follows causes the non-cardia gastric cancer. With that said, by utilizing the ability of the Bacteroides thetaiotaomicron to sense abnormal presence of the H. pylori, early diagnosis or awareness could be extremely beneficial.
Bacteroides thetaiotaomicron
Helicobacter pylori
In order for the early detection of gastric cancer to be effective, B. thetaiotaomicron will undergo CRISPR in order to remove the genes that make it hostile in environments excluding the gut and replacing these genes with the GFP and a promoter. These bacteria can then be ingested by the patient, in which the bacteria will reside in the stomach and utilize response to certain environmental stimuli correlated with population (quorum sensing). One of the other advantages of using the Bacteroides thetaiotaomicron is that it resides in the gut for long periods of time rather than being cycled out often such as bacteria like E. coli. The quorum sensing system is mainly employed by gram negative and gram positive bacteria, or in other words, bacteria that can, or cannot retain a crystal violet stain in the Gram staining method of differentiation. However, because B. thetaiotaomicron is a gram negative bacteria, it is possible for it to utilize quorum sensing in order to control the GFP gene expression when the number of H. pylori bacteria reach quorum. As the H. pylori populations begin to reach quorum, the sudden abundance of signalling molecules (autoinducer-2s) triggers the GFP gene in the B. thetaiotaomicron bacteria. Once the GFP gene of one bacteria has been activated, a gene that produces the B thetaiotaomicron’s own autoinducer-2s will also be activated, leading to activation of other GFP genes in B thetaiotaomicron bacteria. This will eventually cause a bunch of bacteria to fluoresce in solid waste that has been excreted. In this way, diagnosis of non-cardia gastric cancer can be efficiently done without going through scanning machines, biopsies, endoscopies, and other more tedious methods. Also, it can lead to early detection before the lethal stage of metastasis has been reached.
||
Autoinducer
250px-AI-2.png
250px-AI-2.png
GFP Promoter
IMAGE - Molecule - GFP + FlAsH - 02.gif
IMAGE - Molecule - GFP + FlAsH - 02.gif
1
1
0
0
Current methods of gastric cancer diagnosis include both endoscopies and endoscopic ultrasounds, in which probes are inserted through the mouth and used to check for the presence or spread of cancer. If abnormal growth or severe inflammation is present, biopsies can then be performed to yield a definite result. However these methods are not always useful for early detection before bacteria are able to metastasize. Furthermore, MIT has recently used engineered bacteria that can penetrate and grow in the tumor’s environment in order to express gene for a lacZ enzyme which acts on galactose that is linked to luciferin (already injected into patient). They implemented this design into E coli so that, once the galactose has been cleaved, it will be able to be detected in urine, signifying that the patient has developed cancer.
The uses for bacterial computing are endless, from solving complex math problems, to being used in practical situations to aid in medical advancements, the possibilities are endless. As both bacterial computing and synthetic biology continue to advance, the useful and revolutionary applications of these fields will be tremendous.
My name is Eileen Liang, and I'm a rising sophomore at Roy C. Ketcham High School in upstate NY. I'm looking forward to an extremely positive and educationally stimulating session at BLI! Not only am I excited for the content of the camp, but am also anticipating working alongside other such motivated and intelligent students. Quickly following my introduction the biology in my freshman year, I've become intrigued by biology. Not only has biology quickly become my favorite subject, but the fact that biology is very literally the science of all living things around us has only fueled my passion for the subject. Although I won't be taking AP bio until my junior year, I'm already looking forward to expanding my knowledge of bio and hope to become more involved with biology research. I feel that biology research is extremely relevant in order to continue to improve on modern societies, and the constant additions and revelations found as a result of research is truly motivating and impressive.
I pride myself in my participation in a number of school clubs and teams. For example, I have been on and played second singles on my school's varsity tennis team for 3 years and have made both regionals and sectionals for two of those years. Similarly, I participate in my school Interact team, Model UN and debate club, Science Olympiad, and am the treasurer of our school math team, which placed second at sectionals. Also, over the past year, I have collaborated with three other individuals in order to create a fencing club at our school. Through my participation in these activities, I have thoroughly enjoyed the company of unique and talented individuals as well as the knowledge and collaborative qualities that have come as a result of these activities. A random fact about me is that I work three jobs, and thoroughly enjoy each one of them, such as being a Kumon instructor, a traditional Chinese dance instructor at my local Chinese school and teaching novice tennis at Cross Court Tennis Club.
Bacterial Computing
Biology has long since progressed since its rudimentary beginnings in archaic time periods, fueled by the interests of scientists and researchers to explicate the phenomenons presented by the natural world. However, even despite the numerous and groundbreaking results that have stemmed from researching biology, the potential that the field still holds is almost impossible to measure. One such example arises from the emergence of synthetic biology, a field that only recently has come to light, however the possibilities that stem from it have already begun to shape the future of many industries. One of the most revolutionary idea that was derived from the occurrence of such a field was the ability to utilize manipulation of bacteria in order to compute and solve complex math problems, which would later become known as bacterial computing. One of the first utilization of this technology was through solving the Hamiltonian Path Problem, which upon completion, demonstrated the possibility of using such bacteria to solve a number of issues. The future of bacterial computing is extremely promising, and the complex technology has already been employed by both biologists and engineers in order to diagnosis cancer in early stages.
Hamiltonian Path Problem
The inception of bacterial computing ultimately began when Adleman successfully manipulated the E. coli bacteria to solve a complex math problem known as the Hamiltonian Path Problem (HPP) using seven nodes. This contribution to biology became the essential first in consolidating the ideas of bacterial computing, demonstrating and analyzing the possible options that allowed for the beginnings of the new field. To explain, the Hamilton Path Problem (HPP) occurs as a problem within the mathematical field of graph theory and essentially concerns determining a path (if any) that would pass through all the vertices in an undirected or directed graph. Similarly, the HPP is classified as a NP-complete (nondeterministic polynomial) in which any solutions could easily be proven correct.
The relevance of bacterial computing is justified through its innumerable advantages. The autonomous nature of bacteria, for example, would not necessitate human intervention, and the exponential growth of bacteria would assure and even strengthen the number of processors available to solve a particular problem. Similarly, the ability for bacteria to evolve in changing conditions or in response to challenges demonstrate the versatility of bacterial computing. Not only are bacteria ideal organisms for computation, the process of cell division matches the abilities of a conventional silicon computer algorithm. Not only can the bacteria be programmed in such a way that mimics the parallel processing and increased number of processors that are utilized in current computer algorithms, the alternative choice offers many more options that easily demonstrate more potential than that of the conventional methods.
The usage of mathematical modeling was extremely relevant in conducting the research that allowed for the HPP to be solved using bacterial computing. One such example included questioning of whether the initial orientation and order of the DNA would affect the probability of uncovering a solution to the HPP. In the HPP experiment, many bacteria would be searching for a viable solution through flipping genes catalyzed by the Hin recombinase. Under the assumption that each reversal of adjacent DNA edges was equally likely, the team was able to determine that the probability that any starting configuration would be in the solution state after k flips using a transition matrix. By using this matrix, the scientists were able to find, for example, that a three node and three edge graph could converge to equilibrium quickly at 1/48 (.02 seconds) in approximately 20 flips. These computations demonstrated the feasibility of the experiment, as E. coli could divide every 20 - 30 minutes, and would exceed 20 flips in around 16 hours, even if the Hin recombinase were only to catalyze one reaction per cell cycle. Similarly, it was necessary for researchers to use mathematical modelling in order to determine how many bacteria would be required in order to assure at least one cell with a solution. The result to these questions determined that almost 1 billion plasmids would be required in order to guarantee a 99.9% confidence that one of them would contain a HPP solution.
With that said, in order to solve the HPP, E. coli bacteria were basically transformed into computers that could be programmed to execute algorithms through gene circuits. Furthermore, it was necessary for the bacteria to have the ability to be observed as well as sensitive to the environment. To start, three nodes containing edges on a directed graph were encoded into DNA and immediately shuffled inside a bacterium by a recombination system. Genes were also used as nodes that would fluoresce based on red or green proteins, and researchers then utilized the phenotypes that would express the random ordering of graph edges. If the clones showed success, they would fluoresce yellow, as a result of the combination of red and green fluorescence.
At this point, it became necessary for the team to implement certain abstractions in order to design the bacteria. For example, the DNA segments were used to depict nodes on the directed graph, and were bordered by hixC sites which could be rearranged by the Hin recombinase to generate a random orientation of the edges on the graph. In a second abstraction, each gene, besides the terminal one, was regarded as a split gene (in two). Based on this, a DNA edge terminating on the node would be the location of a five half of a gene, while the DNA edge originating on the node would house a three half of a gene. Similarly, a third abstraction presented a new phenotype by representing a solution to the Hamilton Path Problem with a particular arrangement of DNA.
To begin their first implementation after they were confident of positive results, the researchers began with a simple three node model. For observational purposes, they utilized the RFPs and GFPs as nodes and markers. Between them, hixC sites were placed in order for recombination to occur. The function of the GFP and RFP allowed for the scientists to insert these sites without forfeiting the fluorescence. By inserting these sites, the Hin recombinase would be able to bind to them and in turn, flip or invert the DNA.
From there, by employing the now genetically modified E. coli bacteria, the team began to conduct their proof-of-concept experiment. With a unique Hamiltonian pathway, beginning at the RFP node and travelling via pathway A to the GFP, followed by travel from the GFP to the double transcription terminator, which represented the ending of the pathway, along path B. C, on the other hand, acted as a detractor rather than a path, and diverted the pathway from the RFP to the double transcription terminator. After the successful results from this experiment, the three node three edge model would later be put to use as the control, utilizing the three edges to create DNA constructs.
Preceding the application of the Hin recombinase, expression cassettes were made from the previously existing DNA constructs. Each of these cassettes had the same makeup, consisting of a T7 bacteriophage RNA polymerase promoter, a ribosome binding site, and the 5 half of the RFP node before the first hixC site. After adding edges, the constructs that resulted from the arrangement were named ( ABC, ACB, and BAC), each of which corresponded to a certain phenotype that was expressed in that particular experiment.
Following the successful results from the first experiment, researchers later conducted a multitude of similar experiments involving finding the solutions to the Hamiltonian Path Problem. Not only were they able to demonstrate the modification of bacteria (E. coli) in order to solve complex math problems such as the Hamiltonian Path Problem, but also paved the way to the endless possibilities of bacterial computing.
Design
As demonstrated in the information above, bacterial computing is a highly complex and the future of the field is increasingly promising. Currently, researchers and engineers have worked to utilize the modern technology in order to put it to practical use. In terms of this design project, we will utilize some of the concepts used in bacterial computing such as the implementation of information into bacteria in order to diagnosis gastric cancer.
Gastric cancer, is the formation of malignant cells in the mucosal lining of the stomach, and is more commonly called adenocarcinoma. Similar to the other forms of cancer, the disease begins when a mutation arises in a cell’s DNA and begins to rapidly spread and proliferate. Unlike normal cells, however, these malignant cells do not participate in the normal cell cycle, and completely avoid apoptosis. As a result, these abnormal cells form tumors and after sufficient accumulation, will metastasize and spread to other tissues in the body. Early detection of gastric cancer is often difficult, as the symptoms arise only in the later stages of the disease. Thus, the early diagnosis of adenocarcinoma would be extremely relevant and would immensely increase treatment of the disease. Although it is not prevalent in the United States, gastric cancer is still immensely relevant on a worldwide scale, particularly in developing countries.
Our design project revolves around utilizing Bacteroides thetaiotaomicron bacteria in order to detect the presence of Helicobacter pylori, which also resides in the gut. The former is a kind of bacteria that thrives in the gut, and is actually the most abundant bacteria that resides there. Bacteroides thetaiotaomicron is capable of hydrolyzing indigestible polysaccharides, and also contains an environment sensing membrane that is made up primarily of membrane proteins. H. pylori however, is a bacteria that has coexisted with humans for large amounts of time, and the spiral shaped bacterium lives in the mucosal lining of the stomach. In order to survive in the harsh environment of the stomach, H. pylori secretes the enzyme urease, which converts urea to ammonia, and in turn neutralizes the acidity of the environment. Though the majority of people infected with the H. pylori bacteria will never experience illnesses directly caused by the bacterium, recent studies have labelled the bacteria as a major risk factor for both peptic ulcer disease as well as non-cardia gastric cancer. For example, recent research has determined that those who were infected by the bacteria were eightfold more likely to develop adenocarcinoma. This is most likely due to the release of the toxin CagA which alters the structure of stomach cells in order to host the H. pylori. Although a large majority of H. pylori do not have this ability, the bacteria that evade immune responses are able to inject the toxin using an almost needle like appendage. As the levels of CagA increase, the chronic inflammation that eventually follows causes the non-cardia gastric cancer. With that said, by utilizing the ability of the Bacteroides thetaiotaomicron to sense abnormal presence of the H. pylori, early diagnosis or awareness could be extremely beneficial.
Bacteroides thetaiotaomicron
Helicobacter pylori
In order for the early detection of gastric cancer to be effective, B. thetaiotaomicron will undergo CRISPR in order to remove the genes that make it hostile in environments excluding the gut and replacing these genes with the GFP and a promoter. These bacteria can then be ingested by the patient, in which the bacteria will reside in the stomach and utilize response to certain environmental stimuli correlated with population (quorum sensing). One of the other advantages of using the Bacteroides thetaiotaomicron is that it resides in the gut for long periods of time rather than being cycled out often such as bacteria like E. coli. The quorum sensing system is mainly employed by gram negative and gram positive bacteria, or in other words, bacteria that can, or cannot retain a crystal violet stain in the Gram staining method of differentiation. However, because B. thetaiotaomicron is a gram negative bacteria, it is possible for it to utilize quorum sensing in order to control the GFP gene expression when the number of H. pylori bacteria reach quorum. As the H. pylori populations begin to reach quorum, the sudden abundance of signalling molecules (autoinducer-2s) triggers the GFP gene in the B. thetaiotaomicron bacteria. Once the GFP gene of one bacteria has been activated, a gene that produces the B thetaiotaomicron’s own autoinducer-2s will also be activated, leading to activation of other GFP genes in B thetaiotaomicron bacteria. This will eventually cause a bunch of bacteria to fluoresce in solid waste that has been excreted. In this way, diagnosis of non-cardia gastric cancer can be efficiently done without going through scanning machines, biopsies, endoscopies, and other more tedious methods. Also, it can lead to early detection before the lethal stage of metastasis has been reached.
||
Current methods of gastric cancer diagnosis include both endoscopies and endoscopic ultrasounds, in which probes are inserted through the mouth and used to check for the presence or spread of cancer. If abnormal growth or severe inflammation is present, biopsies can then be performed to yield a definite result. However these methods are not always useful for early detection before bacteria are able to metastasize. Furthermore, MIT has recently used engineered bacteria that can penetrate and grow in the tumor’s environment in order to express gene for a lacZ enzyme which acts on galactose that is linked to luciferin (already injected into patient). They implemented this design into E coli so that, once the galactose has been cleaved, it will be able to be detected in urine, signifying that the patient has developed cancer.
The uses for bacterial computing are endless, from solving complex math problems, to being used in practical situations to aid in medical advancements, the possibilities are endless. As both bacterial computing and synthetic biology continue to advance, the useful and revolutionary applications of these fields will be tremendous.
Sources
http://images.slideplayer.com/22/6368181/slides/slide_5.jpg